code: def test_pop_recommend(ml20m, rng, n_jobs):
      users = rng.choice(ml20m["user"].unique(), 10000, replace=False)
      algo = Popular()
      _log.info("training %s", algo)
      algo.fit(ml20m)
      _log.info("recommending with %s", algo)
      recs = batch.recommend(algo, users, 10, n_jobs=n_jobs)
  
      assert recs["user"].nunique() == 10000
  
file_path: lkpy/tests/test_ml20m.py
imports: import logging
  from pathlib import Path
  from lenskit.datasets import MovieLens
  from lenskit import batch
  from lenskit.algorithms import Recommender
  from lenskit.algorithms.basic import Popular
  from lenskit.algorithms.als import BiasedMF
  import pytest
label_desc: Use image node_id 2 for calling a global function with example usage: test_pop_recommend(ml20m, rng, n_jobs) without return types